FERMILBLAZ - Fermi LAT Gamma-Ray Blazar Classification Catalog

Overview

This database table contains a catalog of classifications for blazar candidates of uncertain type (BCU) detected by the Fermi Large Area Telescope gamma-ray instrument. These classifications have been determined by an Artificial Neural Network machine learning method. The aim of the authors' study was to develop an optimized version of this Artificial Neural Network machine learning method for classifying these blazar candidates. The final result of this study increased the classification performance by about 80% with respect to the method previously used for the classification of uncertain blazars in Chiaro et al. (2016MNRAS.462.3180C, CDS Cat. J/MNRAS/462/3180), leaving only 15 unclassified blazars out of 573 blazar candidates of uncertain type listed in the Fermi LAT 4-Year Source Catalog.

Looking beyond the gamma-ray features of blazars, interesting information can be obtained from a multiwavelength study of the sources and particularly from X-ray and radio flux. In this study the authors tested the possibility to use those two parameters to improve the performance of the network. They did not consider any optical spectroscopy data because, when considering uncertain sources, optical spectra are very often not available or not sufficiently descriptive of the nature of the source.

The gamma-ray flux was obtained by adding five time-integrated fluxes in five bands (0.1-0.3, 0.3-1, 1-3, 3-10, 10-100 GeV) from the 3FGL Catalog (Acero et al. 2015ApJS..218...23A, CDS Cat. J/ApJS/218/23). Radio and X-ray data were obtained from the Fermi LAT 4-Year AGN Catalog 3LAC (Ackermann et al. 2015ApJ...810...14A, CDS Cat. J/ApJ/810/14). Radio fluxes used were measured at frequencies of 1.4 and 0.8 GHz; the X-ray fluxes were measured in the 0.1-2.4keV range.

The complete list of 567 classified BCUs is presented in this table in which sources are ordered by increasing likelihood of a source being a BL Lac.

Catalog Bibcode

2019MNRAS.490.4770K

References

Optimizing neural network techniques in classifying Fermi-LAT gamma-ray sources.
    Kovacevic M., Chiaro G., Cutini S., Tosti G.
   <Mon. Not. R. Astron. Soc., 490, 4770-4777 (2019)>
   =2019MNRAS.490.4770K    (SIMBAD/NED BibCode)

Provenance

This database table was ingested by the HEASARC in May 2023 based upon the CDS Catalog J/MNRAS/490/4770 file table1.dat.

Parameters

Name
The blazar source designation, 3FGL JHHMM.m+DDMM, constructed according to the IAU Specifications for Nomenclature, in which the Right Ascension and Declination have been truncated to 0.1 decimal minutes and 1', respectively. The '3' refers to the four-year catalog (the first-year catalog was '1'; the second-year catalog was '2') and 'FGL' represents Fermi Gamma-ray LAT.

RA
The right ascension of the source in the selected equinox. This was derived by the HEASARC based on the provided Galactic Latitude and Longitude coordinates to a precision of 10^-3 degrees in the originating table.

Dec
The declination of the source in the selected equinox. This was derived by the HEASARC based on the provided Galactic Latitude and Longitude coordinates to a precision of 10^-3 degrees in the originating table.

LII
The galactic longitude of the source, given to a precision of 10^-3 degrees in the originating table.

BII
The galactic latitude of the source, given to a precision of 10^-3 degrees in the originating table.

BLLac_Likelihood
The likelihood value corresponding to the source being classified as a BL Lac source, based on the Artificial Neural Network analysis described in the reference paper.

BLLac_Precision
The precision value corresponding to the source being classified as a BL Lac source, based on the Artificial Neural Network analysis described in the reference paper.

FSRQ_Precision
The precision value corresponding to the source being classified as a flat spectrum radio quasar (FSRQ), based on the Artificial Neural Network analysis described in the reference paper.

Source_Type
The classification for the source based on the Artificial Neural Network analysis completed in this work and designated as follows:

         BCU    =  Blazar candidates of uncertain type
         BL Lac = BL Lacertae
         FSRQ   = Flat Spectrum Radio Quasar

BLLac_Likelihood_C16
The likelihood value corresponding to the source being classified as a BL Lac, based on previous work by Chiaro et al. (2016MNRAS.462.3180C; J/MNRAS/462/3180).

Source_Type_C16
The classification for the source based on previous work by Chiaro et al. (2016MNRAS.462.3180C; J/MNRAS/462/3180), and designated as follows:

         BCU    =  Blazar candidates of uncertain type
         BL Lac = BL Lacertae
         FSRQ   = Flat Spectrum Radio Quasar

Class
The HEASARC Browse object classification, based on the source_type parameter.

Contact Person

Questions regarding the FERMILBLAZ database table can be addressed to the HEASARC Help Desk.

Page Author: Browse Software Development Team
Last Modified: Tuesday, 02-May-2023 14:03:38 EDT